CrossEncoder for Slovene NLI

The model was trained using the SentenceTransformers CrossEncoder class. <br /> It is based on SloBerta, a monolingual Slovene model.

Training

This model was trained on the SI-NLI and the slovene_mnli_snli datasets.<br /> More details and the training script are available here: repo

Performance

The model achieves the following metrics:

• Test accuracy: 77.15
• Dev accuracy: 77.51

Usage

The model can be used for inference using the below code:

from sentence_transformers import CrossEncoder

model = CrossEncoder('jacinthes/cross-encoder-sloberta-si-nli-snli-mnli')
premise = 'Pojdi z menoj v toplice.'
hypothesis = 'Bova lepa bova fit.'
prediction = model.predict([premise, hypothesis])
int2label = {0: 'entailment', 1: 'neutral', 2:'contradiction'}
print(int2label[prediction.argmax()])